BackgroundThe impact of additive-genetic relationships captured by single nucleotide polymorphisms (SNPs) on the accuracy of genomic breeding values (GEBVs) has been demonstrated, but recent studies on data obtained from Holstein populations have ignored this fact. However, this impact and the accuracy of GEBVs due to linkage disequilibrium (LD), which is fairly persistent over generations, must be known to implement future breeding programs.Materials and methodsThe data set used to investigate these questions consisted of 3,863 German Holstein bulls genotyped for 54,001 SNPs, their pedigree and daughter yield deviations for milk yield, fat yield, protein yield and somatic cell score. A cross-validation methodology was applied, where the maximum additive-genetic relationship (amax) between bulls in training and validation was controlled. GEBVs were estimated by a Bayesian model averaging approach (BayesB) and an animal model using the genomic relationship matrix (G-BLUP). The accuracy of GEBVs due to LD was estimated by a regression approach using accuracy of GEBVs and accuracy of pedigree-based BLUP-EBVs.ResultsAccuracy of GEBVs obtained by both BayesB and G-BLUP decreased with decreasing amax for all traits analyzed. The decay of accuracy tended to be larger for G-BLUP and with smaller training size. Differences between BayesB and G-BLUP became evident for the accuracy due to LD, where BayesB clearly outperformed G-BLUP with increasing training size.ConclusionsGEBV accuracy of current selection candidates varies due to different additive-genetic relationships relative to the training data. Accuracy of future candidates can be lower than reported in previous studies because information from close relatives will not be available when selection on GEBVs is applied. A Bayesian model averaging approach exploits LD information considerably better than G-BLUP and thus is the most promising method. Cross-validations should account for family structure in the data to allow for long-lasting genomic based breeding plans in animal and plant breeding.

Among the variants was a nonconservative substitution of lysine by alanine (K232A), with the lysine-encoding allele being associated with higher milk fat content. Haplotype analysis indicated the lysine variant to be ancestral. Two animals that were typed heterozygous (Qq) at the QTL based on marker-assisted QTLgenotyping were heterozygous for the K232A substitution, whereas 14 animals that are most likely qq at the QTL were homozygous for the alanine-encoding allele. An independent association study in Fleckvieh animals confirmed the positive effect of the lysine variant on milk fat content. We consider the nonconservative K232A substitution to be directly responsible for the QTL variation, although our genetic studies cannot provide formal proof.

This study presents a second generation of linkage disequilibrium (LD) map statistics for the whole genome of the Holstein-Friesian population, which has a four times higher resolution compared with that of the maps available so far. We used DNA samples of 810 German Holstein-Friesian cattle genotyped by the Illumina Bovine SNP50K BeadChip to analyse LD structure. A panel of 40 854 (75.6%) markers was included in the final analysis. The pairwise r(2) statistic of SNPs up to 5 Mb apart across the genome was estimated. A mean value of r(2) = 0.30 +/- 0.32 was observed in pairwise distances of <25 kb and it dropped to 0.20 +/- 0.24 at 50-75 kb, which is nearly the average inter-marker space in this study. The proportion of SNPs in useful LD (r(2) > or = 0.25) was 26% for the distance of 50 and 75 kb between SNPs. We found a lower level of LD for SNP pairs at the distance < or =100 kb than previously thought. Analysis revealed 712 haplo-blocks spanning 4.7% of the genome and containing 8.0% of all SNPs. Mean and median block length were estimated as 164 +/- 117 kb and 144 kb respectively. Allele frequencies of the SNPs have a considerable and systematic impact on the estimate of r(2). It is shown that minimizing the allele frequency difference between SNPs reduces the influence of frequency on r(2) estimates. Analysis of past effective population size based on the direct estimates of recombination rates from SNP data showed a decline in effective population size to N(e) = 103 up to approximately 4 generations ago. Systematic effects of marker density and effective population size on observed LD and haplotype structure are discussed.

The data from the newly available 50 K SNP chip was used for tagging the genome-wide footprints of positive selection in Holstein-Friesian cattle. For this purpose, we employed the recently described Extended Haplotype Homozygosity test, which detects selection by measuring the characteristics of haplotypes within a single population. To assess formally the significance of these results, we compared the combination of frequency and the Relative Extended Haplotype Homozygosity value of each core haplotype with equally frequent haplotypes across the genome. A subset of the putative regions showing the highest significance in the genome-wide EHH tests was mapped. We annotated genes to identify possible influence they have in beneficial traits by using the Gene Ontology database. A panel of genes, including FABP3, CLPN3, SPERT, HTR2A5, ABCE1, BMP4 and PTGER2, was detected, which overlapped with the most extreme P-values. This panel comprises some interesting candidate genes and QTL, representing a broad range of economically important traits such as milk yield and composition, as well as reproductive and behavioural traits. We also report high values of linkage disequilibrium and a slower decay of haplotype homozygosity for some candidate regions harbouring major genes related to dairy quality. The results of this study provide a genome-wide map of selection footprints in the Holstein genome, and can be used to better understand the mechanisms of selection in dairy cattle breeding.

Various QTL mapping experiments led to the detection of a QTL in the centromeric region of cattle chromosome 14 that had a major effect on the fat content of milk. Recently, the gene encoding diacylglycerol O-acyltransferase (DGAT1) was proposed to be a positional and functional candidate for this trait. This study investigated the effects of a nonconservative lysine to alanine (K232A) substitution in DGAT1, which very likely represents the causal mutation, on milk production traits. Existing granddaughter designs for Fleckvieh and German Holstein, the two major dairy/dual-purpose breeds in Germany, were used to estimate allele frequencies and gene substitution effects for milk, fat, and protein yield, as well as fat and protein content. A restriction fragment length polymorphism assay was applied to diagnose the K232A substitution in DGAT1. Estimates of the allele frequencies for the lysine-encoding variant were based on maternally inherited alleles in sons and amounted to 0.072 for Fleckvieh and 0.548 for German Holstein. Effects of DGAT1 variants on content traits were pronounced; estimates of the gene substitution effect for the lysine-encoding variant were 0.35 and 0.28% for fat content and 0.10 and 0.06% for protein content in Fleckvieh and German Holstein, respectively. Conversely, negative effects of the lysine variant of -242 to -180 kg for Fleckvieh and -260 to -320 kg for German Holstein were revealed for milk yield from first to third lactation, resulting in enhanced fat yield of 7.5 to 14.8 kg in Fleckvieh and 7.6 to 10.7 kg in German Holstein. For protein yield, however, mainly negative effects of -3.6 to 0.2 kg in Fleckvieh and -4.8 to -5.2 kg in German Holstein were observed. Pearson correlations between residuals of milk yield and content traits were decreased when omitting DGAT1 effects in the analysis, thereby indicating that DGAT1 contributes to negative correlations between these traits. Molecular tests allow for the direct selection among variants; however, the benefits of the alternative alleles depend on economic weights given to the different milk production traits in the breeding goal.

Intramuscular fat content, also assessed as marbling of meat, represents an important beef quality trait. Recent work has mapped a quantitative trait locus (QTL) with an effect on marbling to the centromeric region of bovine chromosome 14, with the gene encoding thyroglobulin (TG) being proposed as a positional and functional candidate gene for this QTL. Recently, the gene encoding diacylglycerol O-acyltransferase (DGAT1), which also has been mapped within the region of the marbling QTL, has been demonstrated to affect the fat content of milk. In the present study, the effects of a 5'-polymorphism of TG and of a lysine/alanine polymorphism of DGAT1 on the fat content of musculus (m.) semitendinosus and m. longissimus dorsi in 55 bovine animals (28 German Holstein and 27 Charolais) has been investigated. Significant effects were found for both candidate genes in both the breeds. These effects seem to be independent of one another because the alleles of the two polymorphisms showed no statistically significant disequilibrium. The DGAT1 effect is mainly on the m. semitendinosus. The TG polymorphism only affects m. longissimus dorsi. However, both intramuscular fat enhancing effects seem to be recessive. The possibility of two linked loci, acting recessively on intramuscular fat content, will require special strategies when selecting for higher marbling scores.

Background'Selection signatures' delimit regions of the genome that are, or have been, functionally important and have therefore been under either natural or artificial selection. In this study, two different and complementary methods--integrated Haplotype Homozygosity Score (|iHS|) and population differentiation index (FST)--were applied to identify traces of decades of intensive artificial selection for traits of economic importance in modern cattle.ResultsWe scanned the genome of a diverse set of dairy and beef breeds from Germany, Canada and Australia genotyped with a 50 K SNP panel. Across breeds, a total of 109 extreme |iHS| values exceeded the empirical threshold level of 5% with 19, 27, 9, 10 and 17 outliers in Holstein, Brown Swiss, Australian Angus, Hereford and Simmental, respectively. Annotating the regions harboring clustered |iHS| signals revealed a panel of interesting candidate genes like SPATA17, MGAT1, PGRMC2 and ACTC1, COL23A1, MATN2, respectively, in the context of reproduction and muscle formation. In a further step, a new Bayesian FST-based approach was applied with a set of geographically separated populations including Holstein, Brown Swiss, Simmental, North American Angus and Piedmontese for detecting differentiated loci. In total, 127 regions exceeding the 2.5 per cent threshold of the empirical posterior distribution were identified as extremely differentiated. In a substantial number (56 out of 127 cases) the extreme FST values were found to be positioned in poor gene content regions which deviated significantly (p < 0.05) from the expectation assuming a random distribution. However, significant FST values were found in regions of some relevant genes such as SMCP and FGF1.ConclusionsOverall, 236 regions putatively subject to recent positive selection in the cattle genome were detected. Both |iHS| and FST suggested selection in the vicinity of the Sialic acid binding Ig-like lectin 5 gene on BTA18. This region was recently reported to be a major QTL with strong effects on productive life and fertility traits in Holstein cattle. We conclude that high-resolution genome scans of selection signatures can be used to identify genomic regions contributing to within- and inter-breed phenotypic variation.

Modern aquaculture recirculation systems (RASs) are a necessary tool to provide sustainable and continuous aquaculture production with low environmental impact. But, productivity and efficiency of such RAS still have to be optimized to ensure economic viability, putting growth performance into the focus. Growth is often reported as absolute (gain per day), relative (percentage increase in size) or specific growth rate (percentage increase in size per day), based on stocking and harvesting data. These functions describe growth very simplified and are inaccurate because intermediate growth data are not considered. In contrast, nonlinear growth models attempt to provide information of growth across different life stages. On the basis of an empirical RAS data set of 150 all‐female turbot reared in an RAS during a period of 340 days of outgrowth, this paper reviews the most commonly used growth rates (relative, absolute, specific), the thermal‐unit growth coefficient and five nonlinear growth functions (logistic, Gompertz, von Bertalanffy, Kanis and Schnute). Goodness of fit is expressed by R2 and as mean percentage deviation. Nonlinear growth models are also compared by their residual standard error (RSE) and the Akaike information criterion. All processed functions are modelled to illustrate the shape of the generated curve and the possibility of the function to realistically predict growth. Further, the biological meaning of their regression parameters is discussed. This way we can point out differences in nonlinear growth models in contrast to purely descriptive growth rates and the specific advantages, disadvantages and possible applications of each function we review.